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Developing an efficient strategy for managing nutrients in less-developed lake watersheds that can balance the need for socioeconomic progress with the protection of aquatic ecosystems has become an urgent research subject for achieving sustainable development. This paper improves the optimization method for environmental and economic management of lake watersheds proposed in our previous research. A spatiotemporal optimization method based on a coupling model consisting of the Soil and Water Assessment Tool, system dynamics model, and objective programming model was applied to an agricultural non-point source (ANPS) pollution control program and a rural sewage treatment program at the Yilong Lake watershed as a case study. A simulation evaluation showed that the efficiency of the previous scheme was significantly improved after conducting spatiotemporal optimization. This scheme was dynamic and distributed, demonstrating an annual and high-resolution control program that can provide a basis for the precise management of ANPS. Although it still requires improvement, a framework for coupling simulation and two-step optimization was achieved in this study. • A framework for coupling simulation and two-step optimization is completed. • Spatiotemporal optimization could significantly improve the scheme, which is output by an objective programming model. • A dynamic and high-resolution NPS control program for paddy fields is obtained. [ABSTRACT FROM AUTHOR]

Wastewater treatment plants (WWTPs) play a critical role in the sustainable development of water resources due to its outstanding ability of removing pollutants from complex influent wastewater and generating clean and safe effluent. This paper innovatively adopted the meta-analysis method in view of published LCA studies to assess the energy use and environmental impacts of WWTPs during their life cycle. The search and screening process determined a useful data source with 54 LCA literatures covering 109 relevant case studies. The meta-analysis results revealed that, compared with other regions, the WWTPs in China have the higher intensity in terms of energy use, global warming potential (GWP), eutrophication potential (EP), acidification potential (AP), photochemical oxidation (PHO), freshwater ecotoxicity potential (FETP) and terrestrial ecotoxicity potential (TETP) categories, implying that the energy conservation and emission reduction strategies are necessary to wastewater treatment industry in China. Moreover, compared with A/A/O and CASS processes, the A/O process consumes less energy and results in lower GWP and AP intensity, but affects adversely the natural water-body protection due to undesirable treatment efficiency. Furthermore, the treatment capacities of medium and large scales (i.e. 5-20 × 104 m3/d) are most reasonable sizes for WWTPs since their intensity of energy use, GWP, EP and AP are under a relatively low level. Finally, a strict effluent discharge standard is highly recommended from the perspective of protecting aquatic environment, although it leads to a higher energy consumption. The findings of this study could provide valuable references for promoting healthy and sustainable wastewater treatment industry. • Meta-analysis was firstly explored for evaluating the energy use and EIs of WWTPs. • Data source included 54 LCA literatures covering 109 independent case studies. • Four physical characteristics associated with WWTPs were in-depth discussed. • Recommendations for design and reconstruction of WWTPs in the future were provided. [ABSTRACT FROM AUTHOR]

Estuarine areas are not only the main gathering point for human sewage but also the place where one-way and two-way fluids interact, thus forming a complex and changeable geochemical physical field. Here, heavy metals (HMs) are adsorbed and desorbed due to physical, chemical, and biochemical processes. However, the adsorption and desorption behavior of HMs in the aquatic environment is complex, and physicochemical processes occurring in the estuarine sediment-water interface control the direction and boundaries of the system. This study analyzed the migration and distribution of HMs in rivers and lakes, and established a Bayesian network model to quantitatively understand the impact of nutrients and key environmental factors on the adsorption-desorption behavior of HMs in lake and estuaries, as well as the competitive relationship between environmental factors. The influence of environmental factors and the occurrence of HMs are both important model inputs. Our findings indicated that the migration risk of Cd in Qinghai Lake was high. Environmental factors such as Cation exchange capacity (CEC), Organic matter (OM), Soluble fluoride (SFL), and pH play the most important role in the adsorption and desorption of HMs. Our findings also indicated that the exchange and activity of HMs in sediments were much higher than in the overlying water. The organic matter content was the most complex environmental factor affecting HMS adsorption and desorption at the water-sediment interface. Additionally, the mass concentration of dissolved oxygen (DO) has a linear relationship with bioavailable HMs in river and lake sediments, but has no linear relationship with the concentration of water-soluble HMs. Interestingly, there are synergistic effects between environmental factors, which directly or indirectly affect the release of bioavailable HMs. However, it is important to determine whether the effects of different environmental factors on the exchange of bioavailable HMs are negative or positive. Our findings suggested that Bayesian network (BN) signals (positive or negative) could provide insights into the transfer direction of metals in the water-sediment interface. [Display omitted] • High migration risk of Cd in Qinghai Lake. • The exchange frequency of HMs in sediment is higher than that in overlying water. • OM is the most complex environmental factor affecting HMs adsorption and desorption. • DO increases, Cu and Zn bioavailability increases. • CEC increases, Cr bioavailability increases. [ABSTRACT FROM AUTHOR]

The water-energy nexus (WEN) system is a large-scale complex system that comes with diverse forms of risks owing to many challenges in the process of maintaining economic-resource-environmental sustainability. First, the rapidly increasing demand for water and energy subjects many regions to the high risk of water and energy shortages. Second, decision makers face difficulties in weighing system benefits and loss risks under a series of stricter water-energy policies. To handle the aforementioned dual risks of WEN, in this study we propose copula-based stochastic downside risk-aversion programming (CSDP) for regional water-energy management. CSDP integrates the superiority of the copula analysis method and downside risk-aversion programming into a framework, which can not only reveal the risk interactions between water resources and energy demand by using copula functions under different probability distributions, even previously unknown correlations, but also control economic risk, tackle systemic uncertainties, and provide an effective linkage between system stability and conflicting economic benefits. The proposed model was applied to a water-energy system case study in Tianjin City, China. Optimal solutions for various water resources and energy demand copulas associated with different scenarios and hierarchical risk levels were examined in the CSDP model. The results showed that water resources have a greater influence than energy on industrial structure adjustment in Tianjin, with consequent effects on system benefits, optimal output value schemes, and environmental protection strategies. In addition, the tertiary industry provides a new opportunity for economic growth based on a large amount of water-energy consumption, and its potential resources and water-air pollution risks also deserve extensive attention. [Display omitted] • A dual risk-aversion programming model for water-energy nexus was established. • Water-energy demand joint risk and systemic economic risk were addressed. • Optimization solutions of various joint-interaction scenarios were obtained. • The proposed model was applied to Tianjin City, China for industrial structure adjustment. [ABSTRACT FROM AUTHOR]

Many lake basins are facing the challenge of mitigating water shortage and water pollution while maintaining economic growth. Existing planning method for water pollution control often focus on how to alleviate water pollution effectively at the lowest cost, but rarely pay attention to the dynamic feedback and synergy effects between water pollution abatement, water conservation and social economy. This article proposes a method which consists of system dynamics model (SDM), Soil and Water Assessment Tool (SWAT) and objective programming model (OPM). It could be used to create insights on basin-wide water problems from a systematic perspective. The case study on Yilong Lake Watershed evaluates the proposed measures in existing local planning, calculates the optimal scheme, and discusses issues including the uncertainty of effectiveness, choice between recycling sewage and transferring outside, and the necessity of restricting food processing industry. This method could be improved on the simulation of social and industrial economy, the simulation of water cycle, and the spatial planning. [Display omitted] • System dynamics model and SWAT were coupled to simulate the environment-economic system. • The conflict and synergy among social economy, water resources and aquatic environment were described. • Limiting industry strictly is an inefficient way to improve sustainability for Yilong lake watershed. • Recycling the wastewater and developing eco-friendly crop farming will help improve the sustainability of the watershed. [ABSTRACT FROM AUTHOR]